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implement webui resuming training

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Former-commit-id: 2d41672ef52414c56c50c8b4fdc442797ba682e9
This commit is contained in:
hiyouga
2023-10-15 04:52:19 +08:00
parent ef248dbe15
commit 31e3805fb8
7 changed files with 42 additions and 26 deletions
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4
src/llmtuner/webui/components/eval.py
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@@ -19,8 +19,8 @@ def create_eval_tab(engine: "Engine") -> Dict[str, "Component"]:
dataset = gr.Dropdown(multiselect=True, scale=4)
data_preview_btn = gr.Button(interactive=False, scale=1)
dataset_dir.change(list_dataset, [dataset_dir], [dataset])
dataset.change(can_preview, [dataset_dir, dataset], [data_preview_btn])
dataset_dir.change(list_dataset, [dataset_dir], [dataset], queue=False)
dataset.change(can_preview, [dataset_dir, dataset], [data_preview_btn], queue=False)
input_elems.update({dataset_dir, dataset})
elem_dict.update(dict(

9
src/llmtuner/webui/components/top.py
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@@ -8,10 +8,9 @@ from llmtuner.webui.utils import can_quantize
if TYPE_CHECKING:
from gradio.components import Component
from llmtuner.webui.engine import Engine
def create_top(engine: "Engine") -> Dict[str, "Component"]:
def create_top() -> Dict[str, "Component"]:
available_models = list(SUPPORTED_MODELS.keys()) + ["Custom"]
config = gr.State(value=load_config())
@@ -38,11 +37,11 @@ def create_top(engine: "Engine") -> Dict[str, "Component"]:
rope_scaling = gr.Dropdown(choices=["none", "linear", "dynamic"], value="none")
model_name.change(
list_checkpoint, [model_name, finetuning_type], [checkpoints]
list_checkpoint, [model_name, finetuning_type], [checkpoints], queue=False
).then(
get_model_path, [config, model_name], [model_path]
get_model_path, [config, model_name], [model_path], queue=False
).then(
get_template, [model_name], [template]
get_template, [model_name], [template], queue=False
) # do not save config since the below line will save
model_path.change(save_config, inputs=[config, lang, model_name, model_path])

14
src/llmtuner/webui/components/train.py
View File

@@ -24,9 +24,9 @@ def create_train_tab(engine: "Engine") -> Dict[str, "Component"]:
dataset = gr.Dropdown(multiselect=True, scale=4)
data_preview_btn = gr.Button(interactive=False, scale=1)
training_stage.change(list_dataset, [dataset_dir, training_stage], [dataset])
dataset_dir.change(list_dataset, [dataset_dir, training_stage], [dataset])
dataset.change(can_preview, [dataset_dir, dataset], [data_preview_btn])
training_stage.change(list_dataset, [dataset_dir, training_stage], [dataset], queue=False)
dataset_dir.change(list_dataset, [dataset_dir, training_stage], [dataset], queue=False)
dataset.change(can_preview, [dataset_dir, dataset], [data_preview_btn], queue=False)
input_elems.update({training_stage, dataset_dir, dataset})
elem_dict.update(dict(
@@ -128,6 +128,7 @@ def create_train_tab(engine: "Engine") -> Dict[str, "Component"]:
output_dir = gr.Textbox()
with gr.Row():
resume_btn = gr.Checkbox(visible=False, interactive=False, value=False)
process_bar = gr.Slider(visible=False, interactive=False)
with gr.Box():
@@ -139,15 +140,16 @@ def create_train_tab(engine: "Engine") -> Dict[str, "Component"]:
input_elems.add(output_dir)
output_elems = [output_box, process_bar]
elem_dict.update(dict(
cmd_preview_btn=cmd_preview_btn, start_btn=start_btn, stop_btn=stop_btn,
output_dir=output_dir, output_box=output_box, loss_viewer=loss_viewer
cmd_preview_btn=cmd_preview_btn, start_btn=start_btn, stop_btn=stop_btn, output_dir=output_dir,
resume_btn=resume_btn, output_box=output_box, loss_viewer=loss_viewer, process_bar=process_bar
))
cmd_preview_btn.click(engine.runner.preview_train, input_elems, output_elems)
start_btn.click(engine.runner.run_train, input_elems, output_elems)
stop_btn.click(engine.runner.set_abort, queue=False)
resume_btn.change(engine.runner.monitor, outputs=output_elems)
process_bar.change(
output_box.change(
gen_plot,
[engine.manager.get_elem("top.model_name"), engine.manager.get_elem("top.finetuning_type"), output_dir],
loss_viewer,